Endorsed by the Special Interest Group on the Lexicon of the Association for Computational Linguistics (SIGLEX)

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Multiword Expressions (MWEs) are a ubiquitous component of natural languages and appear steadily on a daily basis, both in specialized and in general-purpose communication. While easily mastered by native speakers, their interpretation poses a major challenge for automated analysis due to their flexible and heterogeneous nature. Therefore, the automated processing of MWEs is desirable for any natural language application that involves some degree of semantic interpretation, e.g., Machine Translation, Information Extraction, and Question Answering.

In spite of the recent advances in the field, there is a wide range of open problems that prevent MWE treatment techniques from full integration in current NLP systems. In MWE'2010, we will be interested in major challenges in the overall process of MWE treatment, asking for original research related but not limited to the following topics:

* MWE resources: Although underused in most current state-of-the-art approaches, resources are key for developing real-world applications capable of interpreting MWEs. We call for papers describing the process of building MWE resources, constructed both manually and automatically from text corpora; we are also interested in assessing the usability of such resources in various MWE tasks.

* Hybrid approaches: We invite research on integrating heterogeneous MWE treatment techniques and resources in NLP applications. Such hybrid approaches can aim, for example, at the combination of results from symbolic and statistical approaches, at the fusion of manually built and automatically extracted resources, or at the design of language learning techniques.

* Domain adaptation: Real-world NLP applications need to be robust to deal with texts coming from different domains. We thus call for papers assessing the performance of MWE methods across domains or describing domain adaptation techniques for MWEs.

* Multilingualism: Parallel and comparable corpora are gaining popularity as a resource for automatic MWE discovery and treatment. We are also interested in the integration of MWE processing in multilingual applications such as machine translation and multilingual information retrieval, as well as in porting existing monolingual MWE approaches to new languages.